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Typus
Verschleierung
Bearbeiter
Graf Isolan
Gesichtet
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Untersuchte Arbeit:
Seite: 8, Zeilen: 9-41
Quelle: Chacon et al 2006
Seite(n): 352, 353, Zeilen: 352:left col. 4-10.13-19.25-30; right col. 1-6.18-21.24-30.34-40; 353:left col. 1-14.30-31.41-49.51 - right col. 1-2.15-17
Fall and Azzam (1998) used GIS to prepare a map indicating natural risk in the coastal area of Dakar, Senegal. GIS analysis was made in ArcInfo and ArcView (ESRI) to obtain a natural risk map based on three groups of instability factors: hydrogeology, coastal erosion and geotechnical parameters showing six zones of coastal slope dynamics. Also another risk assessment approaches were proposed by Kawakami and Saito (1984), Lee et al. (2001). The presence or absence of instability processes and hazard was proposed as a tool for better land-use planning of a coastal area affected by rapid urban development. Wachal and Hudak (2000) used GIS techniques to assess landsliding in a 1,500-2000 km2 area in Travis Country (USA), based on four factors: slope angle, geology, vegetation and distance to faults. Four classes of relative susceptibility were derived weighting these factors according to their contribution to instability processes. Moreiras (2004) proposed landslide incidence or susceptibility (Moreiras, 2005) zonation for a 1,600 km2 area west of Mendoza city, Argentina, based on air photo interpretation, digital analysis of satellite Spot and Landsat images and field control. The degree of relative susceptibility were assigned from GIS analysis taking into account both lithology and slope angle and a landslide inventory.

A very interesting new GIS methodology was proposed by Parise and Jibson (2000) to obtain a landslide seismic susceptibility rating. An inventory of landslides that occurred during the Northridge earthquake (1994, M: 6.7, California, USA) in the Santa Susana quadrangle was made. Distances to the epicenter fault zone and data about the dynamic intensity were expressed as Arias intensities (Arias, 1970). These were considered as a basis for a landslide susceptibility index (LSI is expressed as the ratio in percentage of the area covered by landslides in each geological unit to the total area of the outcrops of that unit) and landslide frequency index (number of landslide per km2). A zonation of four relative susceptibility classes was obtained with a resolution of 10 * 10 m at a scale of 1:24,000: very high (>2.5% landslide area or >30 LS/ km2), high (1.0–2.5% landslide area or 10–30 LS/km2), moderate (0.5–1.0% landslide area or 3–10 LS/km2) and low (<0.5% landslide area and <3 LS/km2).

GIS based rock fall hazard assessment and analysis was accomplished by many authors, for instance Ayala-Carcedo et al. (2003) analyzed a rock fall front in the Sierra de la Cabrera (Madrid, Spain) by a heuristic approach using ArcInfo (ESRI).

One of the first papers in the United States on a wholly GIS assessment of landslide susceptibility, hazard and risk (Mejıa-Navarro et al., 1994) used weighted factors in algorithms, relating debris flow susceptibility and determinant factors. The research was a pilot project done in ArcInfo (ESRI) and GRASS GIS to test the usefulness of GIS in an integrated planning decision support model evaluating different geological hazards. The base maps were at scales of between 1:4,000 and 1:25,000. Debris flow hazard susceptibility, at a scale 1:24,000, was derived from an algorithm which modeled the influence of several factors.


Arias, A. (1970): A measure of earthquake intensity. In: Hansen RJ (ed) Seismic design for nuclear power plants. Massachusetts Institute of Technology Press, Cambridge, pp 438–483.

Ayala-Carcedo, F. J., Cubillo-Nielsen, S., Alvarez, A., Dominguez, M. J., Lain, L., Lain, R., Ortiz, G. (2003) Large scales rock fall reach susceptibility maps in La Cabrera Sierra (Madrid) performed with GIS and dynamic analysis at 1:5.000. In: Chacon J, Corominas J (eds) Special issue on Landslides and GIS. Nat Hazards 30(3):341–360.

Fall, M., Azzam, R. (1998): Application de la ge´ologie [sic] de l’ingenieur et de SIG a` [sic] l’e´tude [sic] de la stabilite´ [sic] des versants coˆ tier [sic], Dakar, Senegal. In: Moore D, Hungr O (eds) Proceedings of the 8th IAEG Congress, Vancouver. A.A. Balkema, Rotterdam, pp 1011–1018.

Kawakami, H., Saito, Y. (1984): Landslide risk mapping by a quantification method. In: Proceedings of the IVth ISL Toronto, Canada, Vol. 2, pp 535–540.

Lee, S., Min, K. (2001): Statistical analysis of landslide susceptibility at Yongin, Korea. Environ. Geol., 40:1095–1113.

Lee, S., Chang, B., Choi, W., Shin, E. (2001): Regional susceptibility, possibility and risk analysis of landslide in Ulsan metropolitan city, Korea. In: Proceedings of the IGARSS 2001: scanning the present and resolving the future. IEEE, Australia, pp 1690–1692.

MejIa-Navarro, M., Wohl, E.W., Oaks, S. D. (1994): Geological hazards, vulnerability, and risk assessment using GIS: model for Glenwood Springs, Colorado. Geomorphology 10:331–354.

Moreiras, S. M. (2004): Landslide incidence zonation in the Rio Mendoza valley, Mendoza province, Argentina. Earth Surf Processes Landforms 29:255–266.

Moreiras, S. M. (2005): Landslide susceptibility zonation in the Rio Mendoza valley, Argentina. Geomorphology 66:345–357.

Parise, M., Jibson, R.W. (2000): A seismic landslide susceptibility rating of geologic units based on analysis of characteristics of landslides triggered by the 17 January, 1994 Northridge, California earthquake. Eng. Geol., 58:251–270.

Wachal, D. J., Hudak, P. F. (2000): Mapping landslide susceptibility in Travis County, Texas, USA. Geol. Journal 51:245–253.

[Page 352]

Fall and Azzam (1998) used GIS to prepare a map indicating natural risk in the coastal areas of Dakar, Senegal. Geological, hydrogeological and geotechnical surveys at a scale of 1:500, and topographical maps from 1953, 1961, 1977 and 1981 at scales of 1:1,000 to 1:5,000 were all digitised and a GIS analysis was made in Arc/Info and Arc View (ESRI). [...] After identifying the lithological units and areas more affected by landslides, GIS layers were superimposed and analysed to obtain a natural risk map based on three groups of instability factors: hydrogeology, coastal erosion and geotechnical parameters. This map revealed six zones of coastal slope dynamics, with a zone affected by instability processes and symbols showing different risks as active scarps and landslides, earth flows, rock fall, etc. [...] Also another risk assessment approaches were proposed by Kawakami and Saito (1984), Lee et al. (2001b). The presence or absence of instability processes and hazard was proposed as a tool for better land-use planning of a coastal area affected by rapid urban development. [...]

[...]

Moreiras (2004) proposed landslide incidence or susceptibility (Moreiras 2005) zonation for a 1,600 km2 area west of Mendoza city, in the Cordillera Frontal Ranges and Precordillera of Argentina, based on airphoto interpretation, digital analysis of satellite spot and Landsat images and field control. [...] The degrees of relative susceptibility were assigned from GIS analysis of every 200 · 200 m unit taking into account both lithology and slope angle and a landslide inventory. [...]

Wachal and Hudak (2000) used GIS techniques to assess landsliding in a 1,500–2,000 km2 area in Travis County (USA), based on four factors: slope angle, geology, vegetation and distance to faults. Four classes of relative susceptibility were derived weighting these factors (0–1) according to their contribution to instability processes. [...]

A very interesting new GIS methodology was proposed by Parise and Jibson (2000) to obtain a landslide seismic susceptibility rating. An inventory of landslides that occurred during the Northridge earthquake (1994, M: 6,7, California, USA) in the Santa Susana quadrangle was made. Distances to the epicentre fault zone and data about the dynamic intensity were expressed

[Page 353]

as Arias intensities (Arias 1970). These were considered as a basis for a LSI (the ratio in % of the area covered by landslides in each geological unit to the total area of the outcrops of that unit) and landslide frequency index (number of landslide per km2). A zonation of four relative susceptibility classes was obtained with a resolution of 10 x 10 m at a scale of 1:24,000: very high (>2.5% landslide area or >30 ls/ km2), high (1.0–2.5% landslide area or 10–30 ls/km2), moderate (0.5–1.0% landslide area or 3–10 ls/km2) and low (<0.5% landslide area and <3 ls/km2).

Ayala-Carcedo et al. (2003) analysed a rock fall front in the Sierra de la Cabrera (Madrid, Spain) by a heuristic approach using Arc Info (ESRI). [...] Also GIS rockfall hazard assessment and analysis was accomplished by Baillifard et al. (2004), Mene´ndez-Duarte and Marquı´- nez (2002) while GIS avalanche hazard was assessed by Barbolini et al. (2002), Brabec et al. (2001), Evans et al. (2001), McClung (2002a, b) and case studies on debris fall GIS mapping by Bathurst et al. (2003) , He et al. (2003), Hofmeister and Miller (2003), Nakagawa and Takahashi (1997).

[...]

One of the first papers in the United States on a wholly GIS assessment of landslide susceptibility, hazard and risk (Mejía-Navarro et al. 1994) used weighted factors in algorithms, relating debris flow susceptibility and determinant factors. Made in Arc/Info (ESRI) and GRASS GIS, the research was a pilot project to test the usefulness of GIS in an integrated planning decision support model evaluating different geological hazards (H—subsidence, rock fall, debris flows and flows) in an area of 6,500 ha around the city of Glenwood Springs, Garfield County, Colorado. The base maps were at scales of between 1:4,000 and 1:25,000. [...]

Debris flow hazard susceptibility, at a scale 1:24,000, was derived from an algorithm which modelled the influence of factors such as slope angle (slopedf); slope orientation (aspect); [...]


Arias A (1970) A measure of earthquake intensity. In: Hansen RJ (ed) Seismic design for nuclear power plants. Massachusetts Institute of Technology Press, Cambridge, pp 438–483

Ayala-Carcedo FJ, Cubillo-Nielsen S, Alvarez A, Domínguez MJ, Laín L, Laín R, Ortíz G (2003) Large scales rock fall reach susceptibility maps in La Cabrera Sierra (Madrid) performed with GIS and dynamic analysis at 1:5.000. In: Chacon J, Corominas J (eds) Special issue on Landslides and GIS. Nat Hazards 30(3):341–360

Fall M, Azzam R (1998) Application de la géologie de l’ingenieur et de SIG à l’étude de la stabilité des versants côtier, Dakar, Senegal. In: Moore D, Hungr O (eds) Proceedings of the 8th IAEG Congress, Vancouver. A.A. Balkema, Rotterdam, pp 1011–1018

Kawakami H, Saito Y (1984) Landslide risk mapping by a quantification method. In: Proceedings of the IVth ISL Toronto, Canada, vol 2, pp 535–540

Lee S, Chang B, Choi W, Shin E (2001b) Regional susceptibility, possibility and risk analysis of landslide in Ulsan metropolitan city, Korea. In: Proceedings of the IGARSS 2001: scanning the present and resolving the future. IEEE, Australia, pp 1690–1692

Mejía-Navarro M, Wohl EW, Oaks SD (1994) Geological hazards, vulnerability, and risk assessment using GIS: model for Glenwood Springs, Colorado. Geomorphology 10:331–354

Moreiras SM (2004) Landslide incidence zonation in the Rio Mendoza valley, Mendoza province, Argentina. Earth Surf Processes Landforms 29:255–266

Moreiras SM (2005) Landslide susceptibility zonation in the Rio Mendoza valley, Argentina. Geomorphology 66:345–357

Parise M, Jibson RW (2000) A seismic landslide susceptibility rating of geologic units based on analysis of characteristics of landslides triggered by the 17 January, 1994 Northridge, California earthquake. Eng Geol 58:251–270

Wachal DJ, Hudak PF (2000) Mapping landslide susceptibility in Travis County, Texas, USA. GeoJournal 51:245–253

Anmerkungen

Although in most places nearly identical with exactly the same references, no hint is given that this text comes from another source.

Obviously, the copying of the reference for Fall, M., Azzam, R. (1998) led to all the accents being in the wrong place in Hja.

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